I'm working on Prompty.tools (http://prompty.tools), a prompt engineering and management platform where users can search, store and combine building blocks for creating structured AI prompts.
I created the platform because I found myself rewriting the same parts of my prompts (or storing them in a text-file) all the time. Now, with a few simple clicks I can populate all the task-specific fluff (personas, constraints, tones, ...) around the actual task that I want the AI to complete.
The platform is open by default; with the purpose of letting users learn from prompts and building blocks that other users created and use. I don't have any users yet, because I want to complete the MCP and Claude Code Plugin before I start marketing my product.
Other things on the roadmap:
- Teams tier, where teams can privately share prompts and building blocks between them. Currently, your data is either private or public, no targeted sharing.
- LLM integration into the prompt builder to reduce prompt engineering friction even more. Instead of manually searching for, and selecting the building blocks you want to use, you would just start typing your task and let the platform decide what building blocks would best support your prompt. There is still a difference with letting an LLM completely generate the prompt, as we would be using existing building blocks that have real feedback from previous uses.
Letting LLMs loose in the digital realm is something that I am also really interested in. I have a (somewhat art project) platform where different models are let loose without a goal or purpose. They have the freedom to do whatever they want, as long as it can be achieved using bash. [0]
most models are... dumb, for a lack of words, and destroy the system by filling up the storage space before doing anything interesting.
Did you one-shot this using an AI coding agent? If this was really just now created after reading this article and the comments, it's incredibly impressive.
I created the platform because I found myself rewriting the same parts of my prompts (or storing them in a text-file) all the time. Now, with a few simple clicks I can populate all the task-specific fluff (personas, constraints, tones, ...) around the actual task that I want the AI to complete.
The platform is open by default; with the purpose of letting users learn from prompts and building blocks that other users created and use. I don't have any users yet, because I want to complete the MCP and Claude Code Plugin before I start marketing my product.
Other things on the roadmap:
- Teams tier, where teams can privately share prompts and building blocks between them. Currently, your data is either private or public, no targeted sharing.
- LLM integration into the prompt builder to reduce prompt engineering friction even more. Instead of manually searching for, and selecting the building blocks you want to use, you would just start typing your task and let the platform decide what building blocks would best support your prompt. There is still a difference with letting an LLM completely generate the prompt, as we would be using existing building blocks that have real feedback from previous uses.
Let me know what you think!